import magic

5 files changed, 961 insertions, 9 deletions

diff --git a/tablib/__init__.py b/tablib/__init__.py
index c2205b6..dc85527 100644
--- a/tablib/__init__.py
+++ b/tablib/__init__.py
@@ -1,8 +1,16 @@
 """ Tablib.
 """
 
-from tablib.core import (
-    Databook, Dataset, detect, import_set, 
-    InvalidDatasetType, InvalidDimensions, UnsupportedFormat
-)
+import sys
+if sys.version_info[0:1] > (2, 5):
+    from tablib.core import (
+        Databook, Dataset, detect, import_set, 
+        InvalidDatasetType, InvalidDimensions, UnsupportedFormat
+    )
+    
+else:
+    from tablib.core25 import (
+        Databook, Dataset, detect, import_set, 
+        InvalidDatasetType, InvalidDimensions, UnsupportedFormat
+    )
 
diff --git a/tablib/core25.py b/tablib/core25.py
new file mode 100644
index 0000000..4ccf229
--- /dev/null
+++ b/tablib/core25.py
@@ -0,0 +1,816 @@
+# -*- coding: utf-8 -*-
+"""
+    tablib.core
+    ~~~~~~~~~~~
+
+    This module implements the central Tablib objects.
+
+    :copyright: (c) 2011 by Kenneth Reitz.
+    :license: MIT, see LICENSE for more details.
+"""
+
+from copy import copy
+from operator import itemgetter
+
+from tablib import formats
+import collections
+
+try:
+    from collections import OrderedDict
+except ImportError:
+    from tablib.packages.ordereddict import OrderedDict
+
+
+__title__ = 'tablib'
+__version__ = '0.9.4'
+__build__ = 0x000904
+__author__ = 'Kenneth Reitz'
+__license__ = 'MIT'
+__copyright__ = 'Copyright 2011 Kenneth Reitz'
+__docformat__ = 'restructuredtext'
+
+
+class Row(object):
+    """Internal Row object. Mainly used for filtering."""
+
+    __slots__ = ['tuple', '_row', 'tags']
+
+    def __init__(self, row=list(), tags=list()):
+        self._row = list(row)
+        self.tags = list(tags)
+
+    def __iter__(self):
+        return (col for col in self._row)
+
+    def __len__(self):
+        return len(self._row)
+
+    def __repr__(self):
+        return repr(self._row)
+
+    def __getslice__(self, i, j):
+        return self._row[i,j]
+
+    def __getitem__(self, i):
+        return self._row[i]
+
+    def __setitem__(self, i, value):
+        self._row[i] = value
+
+    def __delitem__(self, i):
+        del self._row[i]
+
+    def __getstate__(self):
+        return {slot: [getattr(self, slot) for slot in self.__slots__]}
+
+    def __setstate__(self, state):
+        for (k, v) in list(state.items()): setattr(self, k, v)
+
+    def append(self, value):
+        self._row.append(value)
+
+    def insert(self, index, value):
+        self._row.insert(index, value)
+
+    def __contains__(self, item):
+        return (item in self._row)
+
+    @property
+    def tuple(self):
+        '''Tuple representation of :class:`Row`.'''
+        return tuple(self._row)
+
+    @property
+    def list(self):
+        '''List representation of :class:`Row`.'''
+        return list(self._row)
+
+    def has_tag(self, tag):
+        """Returns true if current row contains tag."""
+
+        if tag == None:
+            return False
+        elif isinstance(tag, str):
+            return (tag in self.tags)
+        else:
+            return bool(len(set(tag) & set(self.tags)))
+                
+
+
+
+class Dataset(object):
+    """The :class:`Dataset` object is the heart of Tablib. It provides all core
+    functionality.
+
+    Usually you create a :class:`Dataset` instance in your main module, and append
+    rows and columns as you collect data. ::
+
+        data = tablib.Dataset()
+        data.headers = ('name', 'age')
+
+        for (name, age) in some_collector():
+            data.append((name, age))
+
+    You can also set rows and headers upon instantiation. This is useful if dealing
+    with dozens or hundres of :class:`Dataset` objects. ::
+
+        headers = ('first_name', 'last_name')
+        data = [('John', 'Adams'), ('George', 'Washington')]
+
+        data = tablib.Dataset(*data, headers=headers)
+
+
+    :param \*args: (optional) list of rows to populate Dataset
+    :param headers: (optional) list strings for Dataset header row
+
+
+    .. admonition:: Format Attributes Definition
+
+     If you look at the code, the various output/import formats are not
+     defined within the :class:`Dataset` object. To add support for a new format, see
+     :ref:`Adding New Formats <newformats>`.
+
+    """
+
+    def __init__(self, *args, **kwargs):
+        self._data = list(Row(arg) for arg in args)
+        self.__headers = None
+
+        # ('title', index) tuples
+        self._separators = []
+        
+        # (column, callback) tuples
+        self._formatters = []
+
+        try:
+            self.headers = kwargs['headers']
+        except KeyError:
+            self.headers = None
+
+        try:
+            self.title = kwargs['title']
+        except KeyError:
+            self.title = None
+
+        self._register_formats()
+
+
+    def __len__(self):
+        return self.height
+
+
+    def __getitem__(self, key):
+        if isinstance(key, str):
+            if key in self.headers:
+                pos = self.headers.index(key) # get 'key' index from each data
+                return [row[pos] for row in self._data]
+            else:
+                raise KeyError
+        else:
+            _results = self._data[key]
+            if isinstance(_results, Row):
+                return _results.tuple
+            else:
+                return [result.tuple for result in _results]
+
+
+    def __setitem__(self, key, value):
+        self._validate(value)
+        self._data[key] = Row(value)
+
+
+    def __delitem__(self, key):
+        if isinstance(key, str):
+
+            if key in self.headers:
+
+                pos = self.headers.index(key)
+                del self.headers[pos]
+
+                for i, row in enumerate(self._data):
+
+                    del row[pos]
+                    self._data[i] = row
+            else:
+                raise KeyError
+        else:
+            del self._data[key]
+
+
+    def __repr__(self):
+        try:
+            return '<%s dataset>' % (self.title.lower())
+        except AttributeError:
+            return '<dataset object>'
+
+
+    @classmethod
+    def _register_formats(cls):
+        """Adds format properties."""
+        for fmt in formats.available:
+            try:
+                try:
+                    setattr(cls, fmt.title, property(fmt.export_set, fmt.import_set))
+                except AttributeError:
+                    setattr(cls, fmt.title, property(fmt.export_set))
+
+            except AttributeError:
+                pass
+
+
+    def _validate(self, row=None, col=None, safety=False):
+        """Assures size of every row in dataset is of proper proportions."""
+        if row:
+            is_valid = (len(row) == self.width) if self.width else True
+        elif col:
+            if len(col) < 1:
+                is_valid = True
+            else:
+                is_valid = (len(col) == self.height) if self.height else True
+        else:
+            is_valid = all((len(x) == self.width for x in self._data))
+
+        if is_valid:
+            return True
+        else:
+            if not safety:
+                raise InvalidDimensions
+            return False
+
+
+    def _package(self, dicts=True):
+        """Packages Dataset into lists of dictionaries for transmission."""
+
+        _data = list(self._data)
+        
+        # Execute formatters
+        if self._formatters:
+            for row_i, row in enumerate(_data):
+                for col, callback in self._formatters:
+                    try:                        
+                        if col is None:
+                            for j, c in enumerate(row):
+                                _data[row_i][j] = callback(c)
+                        else:
+                            _data[row_i][col] = callback(row[col])
+                    except IndexError:
+                        raise InvalidDatasetIndex
+                        
+
+        if self.headers:
+            if dicts:
+                data = [OrderedDict(list(zip(self.headers, data_row))) for data_row in _data]
+            else:
+                data = [list(self.headers)] + list(_data)
+        else:
+            data = [list(row) for row in _data]
+
+        return data
+
+
+    def _clean_col(self, col):
+        """Prepares the given column for insert/append."""
+
+        col = list(col)
+
+        if self.headers:
+            header = [col.pop(0)]
+        else:
+            header = []
+
+        if len(col) == 1 and isinstance(col[0], collections.Callable):
+            col = list(map(col[0], self._data))
+        col = tuple(header + col)
+
+        return col
+
+
+    @property
+    def height(self):
+        """The number of rows currently in the :class:`Dataset`.
+           Cannot be directly modified.
+        """
+        return len(self._data)
+
+
+    @property
+    def width(self):
+        """The number of columns currently in the :class:`Dataset`.
+           Cannot be directly modified.
+        """
+
+        try:
+            return len(self._data[0])
+        except IndexError:
+            try:
+                return len(self.headers)
+            except TypeError:
+                return 0
+
+
+    def _get_headers(self):
+        """An *optional* list of strings to be used for header rows and attribute names.
+
+        This must be set manually. The given list length must equal :class:`Dataset.width`.
+
+        """
+        return self.__headers
+
+
+    def _set_headers(self, collection):
+        """Validating headers setter."""
+        self._validate(collection)
+        if collection:
+            try:
+                self.__headers = list(collection)
+            except TypeError:
+                raise TypeError
+        else:
+            self.__headers = None
+
+    headers = property(_get_headers, _set_headers)
+
+    def _get_dict(self):
+        """A native Python representation of the :class:`Dataset` object. If headers have 
+        been set, a list of Python dictionaries will be returned. If no headers have been set, 
+        a list of tuples (rows) will be returned instead.
+
+        A dataset object can also be imported by setting the `Dataset.dict` attribute: ::
+
+            data = tablib.Dataset()
+            data.json = '[{"last_name": "Adams","age": 90,"first_name": "John"}]'
+
+        """
+        return self._package()
+
+
+    def _set_dict(self, pickle):
+        """A native Python representation of the Dataset object. If headers have been
+        set, a list of Python dictionaries will be returned. If no headers have been
+        set, a list of tuples (rows) will be returned instead.
+
+        A dataset object can also be imported by setting the :class:`Dataset.dict` attribute. ::
+
+            data = tablib.Dataset()
+            data.dict = [{'age': 90, 'first_name': 'Kenneth', 'last_name': 'Reitz'}]
+
+        """
+
+        if not len(pickle):
+            return
+
+        # if list of rows
+        if isinstance(pickle[0], list):
+            self.wipe()
+            for row in pickle:
+                self.append(Row(row))
+
+        # if list of objects
+        elif isinstance(pickle[0], dict):
+            self.wipe()
+            self.headers = list(pickle[0].keys())
+            for row in pickle:
+                self.append(Row(list(row.values())))
+        else:
+            raise UnsupportedFormat
+
+    dict = property(_get_dict, _set_dict)
+
+
+    @property
+    def xls():
+        """An Excel Spreadsheet representation of the :class:`Dataset` object, with :ref:`seperators`. Cannot be set.
+
+         .. admonition:: Binary Warning
+
+             :class:`Dataset.xls` contains binary data, so make sure to write in binary mode::
+
+                with open('output.xls', 'wb') as f:
+                    f.write(data.xls)'
+        """
+        pass
+
+
+    @property
+    def csv():
+        """A CSV representation of the :class:`Dataset` object. The top row will contain
+        headers, if they have been set. Otherwise, the top row will contain
+        the first row of the dataset.
+
+        A dataset object can also be imported by setting the :class:`Dataset.csv` attribute. ::
+
+            data = tablib.Dataset()
+            data.csv = 'age, first_name, last_name\\n90, John, Adams'
+
+        Import assumes (for now) that headers exist.
+        """
+        pass
+
+
+    @property
+    def tsv():
+        """A TSV representation of the :class:`Dataset` object. The top row will contain
+        headers, if they have been set. Otherwise, the top row will contain
+        the first row of the dataset.
+
+        A dataset object can also be imported by setting the :class:`Dataset.tsv` attribute. ::
+
+            data = tablib.Dataset()
+            data.tsv = 'age\tfirst_name\tlast_name\\n90\tJohn\tAdams'
+
+        Import assumes (for now) that headers exist.
+        """
+
+    @property
+    def yaml():
+        """A YAML representation of the :class:`Dataset` object. If headers have been
+        set, a YAML list of objects will be returned. If no headers have
+        been set, a YAML list of lists (rows) will be returned instead.
+
+        A dataset object can also be imported by setting the :class:`Dataset.json` attribute: ::
+
+            data = tablib.Dataset()
+            data.yaml = '- {age: 90, first_name: John, last_name: Adams}'
+
+        Import assumes (for now) that headers exist.
+        """
+        pass
+
+
+    @property
+    def json():
+        """A JSON representation of the :class:`Dataset` object. If headers have been
+        set, a JSON list of objects will be returned. If no headers have
+        been set, a JSON list of lists (rows) will be returned instead.
+
+        A dataset object can also be imported by setting the :class:`Dataset.json` attribute: ::
+
+            data = tablib.Dataset()
+            data.json = '[{age: 90, first_name: "John", liast_name: "Adams"}]'
+
+        Import assumes (for now) that headers exist.
+        """
+
+    @property
+    def html():
+        """A HTML table representation of the :class:`Dataset` object. If
+        headers have been set, they will be used as table headers.
+
+        ..notice:: This method can be used for export only.
+        """
+        pass
+
+
+    def append(self, row=None, col=None, header=None, tags=list()):
+        """Adds a row or column to the :class:`Dataset`.
+        Usage is  :class:`Dataset.insert` for documentation.
+        """
+
+        if row is not None:
+            self.insert(self.height, row=row, tags=tags)
+        elif col is not None:
+            self.insert(self.width, col=col, header=header)
+
+
+    def insert_separator(self, index, text='-'):
+        """Adds a separator to :class:`Dataset` at given index."""
+
+        sep = (index, text)
+        self._separators.append(sep)
+
+
+    def append_separator(self, text='-'):
+        """Adds a :ref:`seperator <seperators>` to the :class:`Dataset`."""
+
+        # change offsets if headers are or aren't defined
+        if not self.headers:
+            index = self.height if self.height else 0
+        else:
+            index = (self.height + 1) if self.height else 1
+
+        self.insert_separator(index, text)
+
+
+    def add_formatter(self, col, handler):
+        """Adds a :ref:`formatter` to the :class:`Dataset`.
+        
+        .. versionadded:: 0.9.5
+           :param col: column to. Accepts index int or header str.
+           :param handler: reference to callback function to execute 
+           against each cell value.
+        """
+        
+        if isinstance(col, str):
+            if col in self.headers:
+                col = self.headers.index(col) # get 'key' index from each data
+            else:
+                raise KeyError
+        
+        if not col > self.width:
+            self._formatters.append((col, handler))
+        else:
+            raise InvalidDatasetIndex
+        
+        return True
+        
+
+    def insert(self, index, row=None, col=None, header=None, tags=list()):
+        """Inserts a row or column to the :class:`Dataset` at the given index.
+
+        Rows and columns inserted must be the correct size (height or width).
+
+        The default behaviour is to insert the given row to the :class:`Dataset`
+        object at the given index. If the ``col`` parameter is given, however,
+        a new column will be insert to the :class:`Dataset` object instead.
+
+        You can also insert a column of a single callable object, which will
+        add a new column with the return values of the callable each as an
+        item in the column. ::
+
+            data.append(col=random.randint)
+
+        See :ref:`dyncols` for an in-depth example.
+
+        .. versionchanged:: 0.9.0
+           If inserting a column, and :class:`Dataset.headers` is set, the
+           header attribute must be set, and will be considered the header for
+           that row.
+
+        .. versionadded:: 0.9.0
+           If inserting a row, you can add :ref:`tags <tags>` to the row you are inserting.
+           This gives you the ability to :class:`filter <Dataset.filter>` your
+           :class:`Dataset` later.
+
+        """
+        if row:
+            self._validate(row)
+            self._data.insert(index, Row(row, tags=tags))
+        elif col:
+            col = list(col)
+
+            # Callable Columns...
+            if len(col) == 1 and isinstance(col[0], collections.Callable):
+                col = list(map(col[0], self._data))
+
+            col = self._clean_col(col)
+            self._validate(col=col)
+
+            if self.headers:
+                # pop the first item off, add to headers
+                if not header:
+                    raise HeadersNeeded()
+                self.headers.insert(index, header)
+
+            if self.height and self.width:
+
+                for i, row in enumerate(self._data):
+
+                    row.insert(index, col[i])
+                    self._data[i] = row
+            else:
+                self._data = [Row([row]) for row in col]
+
+
+    def filter(self, tag):
+        """Returns a new instance of the :class:`Dataset`, excluding any rows
+        that do not contain the given :ref:`tags <tags>`.
+        """
+        _dset = copy(self)
+        _dset._data = [row for row in _dset._data if row.has_tag(tag)]
+
+        return _dset
+
+
+    def sort(self, col, reverse=False):
+        """Sort a :class:`Dataset` by a specific column, given string (for
+        header) or integer (for column index). The order can be reversed by
+        setting ``reverse`` to ``True``. 
+        Returns a new :class:`Dataset` instance where columns have been
+        sorted."""
+        
+        if isinstance(col, str):
+
+            if not self.headers:
+                raise HeadersNeeded
+
+            _sorted = sorted(self.dict, key=itemgetter(col), reverse=reverse)
+            _dset = Dataset(headers=self.headers)
+
+            for item in _sorted:
+                row = [item[key] for key in self.headers]
+                _dset.append(row=row)
+
+        else:
+            if self.headers:
+                col = self.headers[col]
+
+            _sorted = sorted(self.dict, key=itemgetter(col), reverse=reverse)
+            _dset = Dataset(headers=self.headers)
+
+            for item in _sorted:
+                if self.headers:
+                    row = [item[key] for key in self.headers]
+                else:
+                    row = item
+                _dset.append(row=row)
+
+
+        return _dset
+
+
+    def transpose(self):
+        """Transpose a :class:`Dataset`, turning rows into columns and vice
+        versa, returning a new ``Dataset`` instance. The first row of the
+        original instance becomes the new header row."""
+
+        # Don't transpose if there is no data
+        if not self:
+            return
+
+        _dset = Dataset()
+        # The first element of the headers stays in the headers,
+        # it is our "hinge" on which we rotate the data
+        new_headers = [self.headers[0]] + self[self.headers[0]]
+
+        _dset.headers = new_headers
+        for column in self.headers:
+
+            if column == self.headers[0]:
+                # It's in the headers, so skip it
+                continue
+
+            # Adding the column name as now they're a regular column
+            row_data = [column] + self[column]
+            row_data = Row(row_data)
+            _dset.append(row=row_data)
+
+        return _dset
+
+
+    def stack_rows(self, other):
+        """Stack two :class:`Dataset` instances together by
+        joining at the row level, and return new combined
+        ``Dataset`` instance."""
+
+        if not isinstance(other, Dataset):
+            return
+
+        if self.width != other.width:
+            raise InvalidDimensions
+
+        # Copy the source data
+        _dset = copy(self)
+
+        rows_to_stack = [row for row in _dset._data]
+        other_rows = [row for row in other._data]
+
+        rows_to_stack.extend(other_rows)
+        _dset._data = rows_to_stack
+
+        return _dset
+
+
+    def stack_columns(self, other):
+        """Stack two :class:`Dataset` instances together by
+        joining at the column level, and return a new
+        combined ``Dataset`` instance. If either ``Dataset``
+        has headers set, than the other must as well."""
+
+        if not isinstance(other, Dataset):
+            return
+
+        if self.headers or other.headers:
+            if not self.headers or not other.headers:
+                raise HeadersNeeded
+
+        if self.height != other.height:
+            raise InvalidDimensions
+
+        try:
+            new_headers = self.headers + other.headers
+        except TypeError:
+            new_headers = None
+
+        _dset = Dataset()
+
+        for column in self.headers:
+            _dset.append(col=self[column])
+
+        for column in other.headers:
+            _dset.append(col=other[column])
+
+        _dset.headers = new_headers
+
+        return _dset
+
+
+    def wipe(self):
+        """Removes all content and headers from the :class:`Dataset` object."""
+        self._data = list()
+        self.__headers = None
+
+
+
+class Databook(object):
+    """A book of :class:`Dataset` objects.
+    """
+
+    def __init__(self, sets=None):
+
+        if sets is None:
+            self._datasets = list()
+        else:
+            self._datasets = sets
+
+        self._register_formats()
+
+    def __repr__(self):
+        try:
+            return '<%s databook>' % (self.title.lower())
+        except AttributeError:
+            return '<databook object>'
+
+
+    def wipe(self):
+        """Removes all :class:`Dataset` objects from the :class:`Databook`."""
+        self._datasets = []
+
+
+    @classmethod
+    def _register_formats(cls):
+        """Adds format properties."""
+        for fmt in formats.available:
+            try:
+                try:
+                    setattr(cls, fmt.title, property(fmt.export_book, fmt.import_book))
+                except AttributeError:
+                    setattr(cls, fmt.title, property(fmt.export_book))
+
+            except AttributeError:
+                pass
+
+
+    def add_sheet(self, dataset):
+        """Adds given :class:`Dataset` to the :class:`Databook`."""
+        if type(dataset) is Dataset:
+            self._datasets.append(dataset)
+        else:
+            raise InvalidDatasetType
+
+
+    def _package(self):
+        """Packages :class:`Databook` for delivery."""
+        collector = []
+        for dset in self._datasets:
+            collector.append(OrderedDict(
+                title = dset.title,
+                data = dset.dict
+            ))
+        return collector
+
+
+    @property
+    def size(self):
+        """The number of the :class:`Dataset` objects within :class:`Databook`."""
+        return len(self._datasets)
+
+
+def detect(stream):
+    """Return (format, stream) of given stream."""
+    for fmt in formats.available:
+        try:
+            if fmt.detect(stream):
+                return (fmt, stream)
+        except AttributeError:
+            pass
+    return (None, stream)
+
+
+def import_set(stream):
+    """Return dataset of given stream."""
+    (format, stream) = detect(stream)
+
+    try:
+        data = Dataset()
+        format.import_set(data, stream)
+        return data
+
+    except AttributeError:
+        return None
+
+
+class InvalidDatasetType(Exception):
+    "Only Datasets can be added to a DataBook"
+
+
+class InvalidDimensions(Exception):
+    "Invalid size"
+    
+class InvalidDatasetIndex(Exception):
+    "Outside of Dataset size"
+
+class HeadersNeeded(Exception):
+    "Header parameter must be given when appending a column in this Dataset."
+
+class UnsupportedFormat(NotImplementedError):
+    "Format is not supported"
diff --git a/tablib/formats/_json.py b/tablib/formats/_json.py
index 262c627..8d498df 100644
--- a/tablib/formats/_json.py
+++ b/tablib/formats/_json.py
@@ -3,8 +3,13 @@
 """ Tablib - JSON Support
 """
 
-import tablib.core
-from tablib.packages import anyjson
+import tablib
+
+import sys
+if sys.version_info[:2] > (2, 5):
+    from tablib.packages import anyjson
+else:
+    from tablib.packages import anyjson25 as anyjson
 
 
 
@@ -34,7 +39,7 @@ def import_book(dbook, in_stream):
 
     dbook.wipe()
     for sheet in anyjson.deserialize(in_stream):
-        data = tablib.core.Dataset()
+        data = tablib.Dataset()
         data.title = sheet['title']
         data.dict = sheet['data']
         dbook.add_sheet(data)
diff --git a/tablib/packages/anyjson25.py b/tablib/packages/anyjson25.py
new file mode 100644
index 0000000..ad6fc40
--- /dev/null
+++ b/tablib/packages/anyjson25.py
@@ -0,0 +1,118 @@
+u"""
+Wraps the best available JSON implementation available in a common interface
+"""
+
+__version__ = u"0.2.0"
+__author__ = u"Rune Halvorsen <runefh@gmail.com>"
+__homepage__ = u"http://bitbucket.org/runeh/anyjson/"
+__docformat__ = u"restructuredtext"
+
+u"""
+
+.. function:: serialize(obj)
+
+    Serialize the object to JSON.
+
+.. function:: deserialize(str)
+
+    Deserialize JSON-encoded object to a Python object.
+
+.. function:: force_implementation(name)
+
+    Load a specific json module. This is useful for testing and not much else
+
+.. attribute:: implementation
+
+    The json implementation object. This is probably not useful to you,
+    except to get the name of the implementation in use. The name is
+    available through `implementation.name`.
+"""
+
+import sys
+from itertools import izip
+
+implementation = None
+
+u"""
+.. data:: _modules
+
+    List of known json modules, and the names of their serialize/unserialize
+    methods, as well as the exception they throw. Exception can be either
+    an exception class or a string.
+"""
+_modules = [(u"cjson", u"encode", u"EncodeError", u"decode", u"DecodeError"),
+            (u"jsonlib2", u"write", u"WriteError", u"read", u"ReadError"),
+            (u"jsonlib", u"write", u"WriteError", u"read", u"ReadError"),
+            (u"simplejson", u"dumps", TypeError, u"loads", ValueError),
+            (u"json", u"dumps", TypeError, u"loads", ValueError),
+            (u"django.utils.simplejson", u"dumps", TypeError, u"loads",
+             ValueError)]
+_fields = (u"modname", u"encoder", u"encerror", u"decoder", u"decerror")
+
+
+class _JsonImplementation(object):
+    u"""Incapsulates a JSON implementation"""
+
+    def __init__(self, modspec):
+        modinfo = dict(list(izip(_fields, modspec)))
+
+        # No try block. We want importerror to end up at caller
+        module = self._attempt_load(modinfo[u"modname"])
+
+        self.implementation = modinfo[u"modname"]
+        self._encode = getattr(module, modinfo[u"encoder"])
+        self._decode = getattr(module, modinfo[u"decoder"])
+        self._encode_error = modinfo[u"encerror"]
+        self._decode_error = modinfo[u"decerror"]
+
+        if isinstance(modinfo[u"encerror"], unicode):
+            self._encode_error = getattr(module, modinfo[u"encerror"])
+        if isinstance(modinfo[u"decerror"], unicode):
+            self._decode_error = getattr(module, modinfo[u"decerror"])
+
+        self.name = modinfo[u"modname"]
+
+    def _attempt_load(self, modname):
+        u"""Attempt to load module name modname, returning it on success,
+        throwing ImportError if module couldn't be imported"""
+        __import__(modname)
+        return sys.modules[modname]
+
+    def serialize(self, data):
+        u"""Serialize the datastructure to json. Returns a string. Raises
+        TypeError if the object could not be serialized."""
+        try:
+            return self._encode(data)
+        except self._encode_error, exc:
+            raise TypeError(*exc.args)
+
+    def deserialize(self, s):
+        u"""deserialize the string to python data types. Raises
+        ValueError if the string vould not be parsed."""
+        try:
+            return self._decode(s)
+        except self._decode_error, exc:
+            raise ValueError(*exc.args)
+
+
+def force_implementation(modname):
+    u"""Forces anyjson to use a specific json module if it's available"""
+    global implementation
+    for name, spec in [(e[0], e) for e in _modules]:
+        if name == modname:
+            implementation = _JsonImplementation(spec)
+            return
+    raise ImportError(u"No module named: %s" % modname)
+
+
+for modspec in _modules:
+    try:
+        implementation = _JsonImplementation(modspec)
+        break
+    except ImportError:
+        pass
+else:
+    raise ImportError(u"No supported JSON module found")
+
+serialize = lambda value: implementation.serialize(value)
+deserialize = lambda value: implementation.deserialize(value)
diff --git a/tox.ini b/tox.ini
index ce52a01..764ee3c 100644
--- a/tox.ini
+++ b/tox.ini
@@ -1,12 +1,17 @@
 [tox]
-envlist = py24,py25,py26,py27, py3
+envlist = py25,py26,py27,py3
 
 [testenv]
 commands=py.test --junitxml=junit-{envname}.xml
 deps = pytest
     
+[testenv:py25]
+simplejson = pytest simplejson
+
 [testenv:pypy]
 basepython=/usr/bin/pypy-c
+simplejson = pytest simplejson
 
 [testenv:py3]
-basepython=/usr/bin/python3
\ No newline at end of file
+basepython=/usr/bin/python3
+simplejson = pytest
\ No newline at end of file